Intelligent detection method for tapping omitting of internal thread based on computer vision

2019 ◽  
Vol 32 (3/4) ◽  
pp. 238-243
Author(s):  
Wei Ding ◽  
Qingguo Wang ◽  
Yanfang Zhao
Keyword(s):  
Computer Vision ◽  
Detection Method ◽  
Internal Thread ◽  
Intelligent Detection

scholarly journals Random Forest with Adaptive Local Template for Pedestrian Detection

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Tao Xiang ◽  
Tao Li ◽  
Mao Ye ◽  
Zijian Liu
Keyword(s):  
Computer Vision ◽  
Random Forest ◽  
Classification Accuracy ◽  
Template Matching ◽  
Detection Method ◽  
State Of The Art ◽  
Pedestrian Detection ◽  
Sliding Window ◽  
Experimental Results ◽  
Training Samples

Pedestrian detection with large intraclass variations is still a challenging task in computer vision. In this paper, we propose a novel pedestrian detection method based on Random Forest. Firstly, we generate a few local templates with different sizes and different locations in positive exemplars. Then, the Random Forest is built whose splitting functions are optimized by maximizing class purity of matching the local templates to the training samples, respectively. To improve the classification accuracy, we adopt a boosting-like algorithm to update the weights of the training samples in a layer-wise fashion. During detection, the trained Random Forest will vote the category when a sliding window is input. Our contributions are the splitting functions based on local template matching with adaptive size and location and iteratively weight updating method. We evaluate the proposed method on 2 well-known challenging datasets: TUD pedestrians and INRIA pedestrians. The experimental results demonstrate that our method achieves state-of-the-art or competitive performance.

scholarly journals New Edge Detection Method for Indonesian Batik

2011 ◽  
Vol 2 (1) ◽  
Author(s):  
Thomas Adi Purnomo Shidi ◽  
Suyoto Suyoto
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Edge Detection ◽  
Detection Method ◽  
New Method ◽  
Analysis Method ◽  
Unique Pattern ◽  
Detection Analysis ◽  
Edge Detection Method

Abstrak. Metode Baru Deteksi Tepi untuk Batik Indonesia. Didalam paper ini, diusulkan sebuah metode pendeteksi baru untuk motif batik. Deteksi tepi sudah sangat sering digunakan didalam pemrosesan gambar. Batik motif adalah salah satu contoh gambar yang memiliki bentuk yang unik dan menarik untuk dianalisis. Metode yang digunakan pada paper ini adalam metode canny dan prewit dan akan menghasilkan metode baru yaitu metode Thomas. Perbedaan antara metode dan hasil akan dilihat dari sisi ketepatan, qualitas hasil dan kejelasan. Contoh batik yang akan digunakan adalah motif parang, motife lereng dan udan liris. Ketiga batik tersebut memiliki pola  yang unik. Kata kunci : Canny, Prewitt, Thomas, Batik, Parang, Lereng, Udan liris. Abstract. New Edge Detection Method for Indonesian Batik. In this paper, we propose a new edge detection analysis method on batiks motif. Edge detection has been oftenly  used in computer vision and image processing. Indonesian  Batiks motif are some example of graphic picture that has unique pattern that interesting to analyse. The method that used for example on this paper are canny and prewit and produce a new method, thomas method. the different  amongs the method, the result of comparison appears on quality, accuracy and clarity. The example that we use are parang batiks motive, lereng batiks motive, and udan liris batiks motive. Three of batiks motive above are have unique pattern. Keywords: Canny, Prewitt, Thomas, Batik, Parang, Lereng, Udan liris.

scholarly journals Computer Vision Measurement of Pointer Meter Readings Based on Inverse Perspective Mapping

2019 ◽  
Vol 9 (18) ◽  
pp. 3729 ◽  
Author(s):  
Bao ◽  
Tan ◽  
Liu ◽  
Miao
Keyword(s):  
Computer Vision ◽  
Visual Detection ◽  
Detection Method ◽  
Transformation Matrix ◽  
Normal Vector ◽  
Vision Measurement ◽  
Extrinsic Parameters ◽  
Perspective Effect ◽  
Rotation Transformation ◽  
Inverse Perspective Mapping

A computer vision method for measuring multiple pointer meters is proposed based on the inverse perspective mapping. First, the measured meter scales are used as the calibration objects to obtain the extrinsic parameters of the meter plane. Second, normal vector of the meter plane can be acquired by the extrinsic parameters, obtaining the rotation transformation matrix of the meter image. Then, the acquired meter image is transformed to a position both parallel to the meter plane and near the main point by the rotation transformation matrix and the extrinsic parameters, eliminating the perspective effect of the acquired image. Finally, the transformed image is tested by the visual detection method to obtain the readings of the pointer meter, improving measurement precision. The results of the measurement verify the effectiveness and accuracy of the method.

A data fusion detection method for fish freshness based on computer vision and near-infrared spectroscopy

2016 ◽  
Vol 8 (14) ◽  
pp. 2929-2935 ◽  
Author(s):  
Xingyi Huang ◽  
Haixia Xu ◽  
Lei Wu ◽  
Huang Dai ◽  
Liya Yao ◽  
...  
Keyword(s):  
Computer Vision ◽  
Infrared Spectroscopy ◽  
Data Fusion ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Detection Method ◽  
Spectroscopic Techniques ◽  
Fusion Detection

This article proposes and describes a data fusion detection method based on computer vision and spectroscopic techniques for fish freshness classification.

An Intelligent Detection Method for Network Security

2014 ◽  
Vol 530-531 ◽  
pp. 646-649
Author(s):  
Ling Qiu ◽  
Cai Ming Liu
Keyword(s):  
Network Security ◽  
Immune Cells ◽  
Detection Method ◽  
Network Data ◽  
Network Attacks ◽  
Detection Ability ◽  
Intelligent Detection ◽  
Network Administrators ◽  
Ip Packets

To dynamically discover network attacks hidden in network data, an intelligent detection method for network security is proposed. Biological immune principles and mechanisms are adopted to judge whether network data contain illegal network packets. Signature library of network attacks and section library of attack signatures are constructed. They store attack signatures and signature sections, respectively. They are used to make the initial detection ability of proposed method. Detectors are defined to simulate immune cells. They evolve dynamically to adapt the network security. Signatures of network data are extracted from IP packets. Detectors match network data's signatures which mean some attacks. Warning information is formed and sent to network administrators according to recognized attacks.

Design of Low-Noise, High-Density Signal Intelligent Detection System

2013 ◽  
Vol 380-384 ◽  
pp. 3882-3885
Author(s):  
Xiaoan Yang
Keyword(s):  
Phase Transition ◽  
Detection Method ◽  
Detection System ◽  
Low Noise ◽  
Weak Signal ◽  
High Effectiveness ◽  
Motion State ◽  
Intelligent Detection ◽  
Stable Performance ◽  
Engineering Practices

Using motion state of the equipment transducer to determine the presence of a weak signal is a common method of signal detection, whose core is to determine the system's phase change. There a many traditional ways to judge phase transition, but most of which have computational complexity and need a large amount of data which make them difficult to apply engineering practices. In order to solve these problems, this paper presents a detection method based on Lyapunov exponent classification with a small amount of data. This approach has some advantages such as requiring fewer observed values, small calculation amount, and able to automatically determine the phase transition without subjective factors involved etc. Experiments show that this method has stable performance, high effectiveness, strong practicality and promotion.

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